A Cluster Shared Volume (CSV) is a storage volume that is made accessible for read and write operations by all nodes within a failover cluster. CSVs are extensively used in production environments in hypervisor (e.g., Microsoft Hyper-V) cluster deployments. Since CSVs receive writes from multiple nodes, it is difficult to design conventional block based backup solutions involving both full and incremental backups for them because the writes need to be tracked at multiple locations and these changes need to be collated in the case of incremental backups. Hence, full backs are usually required for CSVs, which result in longer backup windows.
A backup window is the time required to perform and finish a backup, which is directly related to the backup process itself. Typically, depending on the size of data to be backed up, down time (sometimes in the hours) has to be identified in a business process. Backups, being a necessary activity, would lead to definite shrink in productive hours. The snapshot capability at various levels, such as at the volume level or the application level, may reduce down time by enabling backups even during production. But still there is a continuous endeavor to swiftly perform backups of large data sets (ranging in terabytes “TBs” or even more). Further, it has been observed that with conventional backup technologies data is typically sent in a single stream, which would result in under usage of network capabilities.